See comments on github

R/qflag.R

@@ -7,8 +7,7 @@ qflag <- function(loa=loa, nstat) {
   # -- 2) qsorts which square loading is higher than the sum of square loadings of the same q-sort in all other factors
   thold.05 <- 1.96/sqrt(nstat)
   loa_sq <- loa^2
-  flagged <- data.frame(cbind(1:nqsorts))
-  flagged[,1] <- as.logical(flagged[,1])
+  flagged <- matrix(data=F, nrow=nqsorts, ncol=ncol(loa))
   f <- 1
   while (f <= ncol(loa)) {
     n <- 1

R/qmethod.R

@@ -28,44 +28,45 @@ qmethod <- function(dataset, nfactors, extraction="PCA", rotation="varimax", for
   # Run the analysis
   cor.data <- cor(dataset, method=cor.method)
   if(extraction == "PCA") {
-    loa <- as.data.frame(unclass(principal(cor.data, nfactors=nfactors, rotate=rotation, ...)$loadings)) #PCA from {psych} for factor loadings
+    loa <- unclass(principal(cor.data, nfactors=nfactors, rotate=rotation, ...)$loadings) #PCA from {psych} for factor loadings
   }
   if(extraction == "centroid") {
-    loa <- as.data.frame(unclass(centroid(tmat=cor.data, nfactors=nfactors, spc)))
+    loa.unr <- unclass(centroid(tmat=cor.data, nfactors=nfactors, spc))
+    loa <- unclass(varimax(loa.unr[,1:nfactors])$loadings)
   }
   names(loa) <- paste0("f", 1:length(loa))
   # The following depends on the qmethod functions: qflag, qzscores, qfcharact, qdc
   flagged <- qflag(loa=loa, nstat=nstat)
   qmethodresults <- qzscores(dataset, nfactors, flagged=flagged, loa=loa, forced=forced, distribution=distribution)
   if(extraction == "PCA") qmethodresults$brief$extraction <- extraction
   if(extraction == "centroid") qmethodresults$brief$extraction <- paste0(extraction, " (threshold = ", spc, ")")
-  qmethodresults$brief$rotation   <- rotation
-  qmethodresults$brief$flagging   <- "automatic"
-  qmethodresults$brief$cor.method <- cor.method
+  qmethodresults$brief$rotation    <- rotation
+  qmethodresults$brief$flagging    <- "automatic"
+  qmethodresults$brief$cor.method  <- cor.method
   qmethodresults$brief$pkg.version <- packageVersion('qmethod')
-  qmethodresults$brief$info <- c("Q-method analysis.",
-                                 paste0("Finished on:               ",
-                                        qmethodresults$brief$date),
-                                 paste0("'qmethod' package version: ",
-                                        qmethodresults$brief$pkg.version),
-                                 paste0("Original data:             ",
-                                        qmethodresults$brief$nstat,
-                                        " statements, ",
-                                        qmethodresults$brief$nqsorts, " Q-sorts"),
-                                 paste0("Forced distribution:       ",
-                                        qmethodresults$brief$distro),
-                                 paste0("Number of factors:         ",
-                                        qmethodresults$brief$nfactors),
-                                 paste0("Extraction:                ",
-                                        qmethodresults$brief$extraction),
-                                 paste0("Rotation:                  ",
-                                        qmethodresults$brief$rotation),
-                                 paste0("Flagging:                  ",
-                                        qmethodresults$brief$flagging),
-                                 paste0("Correlation coefficient:   ",
-                                        qmethodresults$brief$cor.method))
+  qmethodresults$brief$info        <- c("Q-method analysis.",
+                                        paste0("Finished on:               ",
+                                               qmethodresults$brief$date),
+                                        paste0("'qmethod' package version: ",
+                                               qmethodresults$brief$pkg.version),
+                                        paste0("Original data:             ",
+                                               qmethodresults$brief$nstat,
+                                               " statements, ",
+                                               qmethodresults$brief$nqsorts, " Q-sorts"),
+                                        paste0("Forced distribution:       ",
+                                               qmethodresults$brief$distro),
+                                        paste0("Number of factors:         ",
+                                               qmethodresults$brief$nfactors),
+                                        paste0("Extraction:                ",
+                                               qmethodresults$brief$extraction),
+                                        paste0("Rotation:                  ",
+                                               qmethodresults$brief$rotation),
+                                        paste0("Flagging:                  ",
+                                               qmethodresults$brief$flagging),
+                                        paste0("Correlation coefficient:   ",
+                                               qmethodresults$brief$cor.method))
   qmethodresults[[8]] <- qdc(dataset, nfactors, zsc=qmethodresults$zsc, 
-                             sed=as.data.frame(qmethodresults$f_char$sd_dif))
+                             sed=qmethodresults$f_char$sd_dif)
   names(qmethodresults)[8] <- "qdc"
   if (silent== FALSE) cat(qmethodresults$brief$info, sep="\n")
   return(qmethodresults)

R/qzscores.R

@@ -76,18 +76,22 @@ qzscores <- function(dataset, nfactors, loa, flagged, forced = TRUE, distributio
   f_char <- qfcharact(loa, flagged, zsc, nfactors, floa)
   #F. FINAL OUTPUTS
   brief <- list()
-  brief$date <- date()
-  brief$nstat <- nstat
-  brief$nqsorts <- nqsorts
-  brief$distro <- forced
-  brief$nfactors <- nfactors
-  brief$rotation <- "Unknown: loadings were provided separately."
-  brief$cor.method <- "Unknown: loadings were provided separately."
+  brief$date        <- date()
+  brief$pkg.version <- packageVersion('qmethod')
+  brief$nstat       <- nstat
+  brief$nqsorts     <- nqsorts
+  brief$distro      <- forced
+  brief$nfactors    <- nfactors
+  brief$extraction  <- "Unknown: loadings were provided separately."
+  brief$rotation    <- "Unknown: loadings were provided separately."
+  brief$cor.method  <- "Unknown: loadings were provided separately."
   brief$info <- c("Q-method z-scores.",
                   paste0("Finished on:             ", brief$date), 
+                  paste0("'qmethod' package version: ", brief$pkg.version),
                   paste0("Original data:           ", brief$nstat, " statements, ", brief$nqsorts, " Q-sorts"),
                   paste0("Forced distribution:     ", brief$distro),
                   paste0("Number of factors:       ", brief$nfactors),
+                  paste0("Extraction:              ", brief$extraction),
                   paste0("Rotation:                ", brief$rotation),
                   paste0("Flagging:                Unknown: flagged Q-sorts were provided separately."),
                   paste0("Correlation coefficient: ", brief$cor.method))

man/centroid.Rd

@@ -1,20 +1,23 @@
 \name{centroid}
 \alias{centroid}
 \title{Q methodology: centroid extraction}
-\description{Extracts factors using the centroid approach.}
+\description{Extracts factors/ components using the centroid approach as an alternative to Principal Components Analysis.}
 \usage{centroid(tmat, nfactors = 7, spc)}
 
 \arguments{
   \item{tmat}{a correlation matrix between Q-sorts.}
-  \item{nfactors}{number of factors/ components to extract.}
+  \item{nfactors}{number of factors/ components to extract. Defaults to 7.}
   \item{spc}{the threshold to accept factor results, set to 0.005 by default (in Brown 1980, this is set to 0.02).}
 }
 
-\details{In order to implement manual flagging, use a manually created data frame for \code{flagged}. See an example of code to perform manual flagging or to manipulate the loadings in \url{https://github.com/aiorazabala/qmethod/wiki/Advanced-analysis}.
+\details{This functions implement the centroid method for extraction of factors, an alternative to Principal Components that can be used in Q methodology. The calculations are based in Brown (1980; below). 
 
-The loadings from \code{principal(...)$loadings} can be explored to decide upon flagging. The \code{loa} data frame should have Q-sorts as rows, and factors as columns, where \code{TRUE} are the flagged Q-sorts.}
+The function is called from within \code{\link{qmethod}} where the attribute \code{extraction} is set to \code{centroid}.
+
+This function can be used independently where conducting each step of the analysis separately, preceded by a correlation between Q-sorts and followed by the rotation of factors/ components (see below), calculation of z-scores, etc.
+}
 \value{
-Returns a matrix with Q-sorts as rows, and rotated factors as columns
+Returns a matrix with Q-sorts as rows, and rotated factors as columns.
 }
 \references{Brown, S. R., 1980 \emph{Political subjectivity: Applications of Q methodology in political science}, New Haven, CT: Yale University Press, pages 208-224.
 
@@ -29,13 +32,34 @@ See further references on the methodology in \code{\link{qmethod-package}}.}
 require('qmethod')
 require ("psych")
 
+# Load data
 data("lipset")
 lip <- lipset[[1]]
+
+# Correlation matrix
 corlip <-cor(lip)
 
+# Centroid extraction
 lipcent <- centroid(corlip)
 lipcent
 
-# varimax rotation over 3 factors
+
+## To finalise the full analysis, continue with the following steps
+# Rotation (in this example, varimax over 3 factors)
 vmax <- varimax(lipcent[,1:3])
-qflag (unclass(vmax$loadings), nstat = 33)}
+
+# Automatic pre-flagging of Q-sorts
+flags <- qflag(unclass(vmax$loadings), nstat = 33)
+
+# Calculate z-scores and general characeristics
+results <- qzscores(lip, 3, loa=vmax$loadings, flagged=flags)
+summary(results)
+
+# Consensus and distinguishing statements
+results$qdc <- qdc(lip, 3, zsc=results$zsc, sed=as.data.frame(results$f_char$sd_dif))
+
+plot(results)
+
+## All of the above can be done with:
+results2 <- qmethod(lip, 3, extraction="centroid")
+}